code: def get_all_embeddings(
      self, dataset, trunk_model, embedder_model, collate_fn
  ):
      dataloader = c_f.get_eval_dataloader(
          dataset,
          self.batch_size,
          self.dataloader_num_workers,
          collate_fn,
      )
      (
          anchor_embeddings,
          posneg_embeddings,
          labels,
      ) = self.compute_all_embeddings(
          dataloader, trunk_model, embedder_model
      )
      anchor_embeddings, posneg_embeddings = (
          self.maybe_normalize(anchor_embeddings),
          self.maybe_normalize(posneg_embeddings),
      )
      return (
          torch.cat([anchor_embeddings, posneg_embeddings], dim=0),
          torch.cat([labels, labels], dim=0),
      )
  
file_path: pytorch-metric-learning/src/pytorch_metric_learning/testers/global_twostream_embedding_space.py
imports: import torch
  import tqdm
  from ..utils import common_functions
  from .global_embedding_space import GlobalEmbeddingSpaceTester
label_desc: Use image node_id 2 for calling the GlobalTwoStreamEmbeddingSpaceTester obj's underlying member method code with example usage: obj.get_all_embeddings(dataset, trunk_model, embedder_model, collate_fn) and returns: torch,  torch